setPriorParametersBerry: setPriorParametersBerry

In bhmbasket: Bayesian Hierarchical Models for Basket Trials

setPriorParametersBerry

Description

This function sets prior parameters for the analysis method "berry" for use in performAnalyses.

Usage

setPriorParametersBerry(mu_mean, mu_sd, tau_scale)

Arguments

mu_mean	A numeric for the mean of μ
mu_sd	A positive numeric for the standard deviation of μ
tau_scale	A positive numeric for the scale parameter of τ

Details

This function sets the prior parameters for the method proposed by Berry et al. (2013). Note that the implemented distribution of τ is half-normal.

Value

A list with prior parameters of class prior_parameters_list

Author(s)

Stephan Wojciekowski

References

Berry, Scott M., et al. "Bayesian hierarchical modeling of patient subpopulations: efficient designs of phase II oncology clinical trials." Clinical Trials 10.5 (2013): 720-734.

See Also

performAnalyses getPriorParameters combinePriorParameters setPriorParametersExNex setPriorParametersExNexAdj setPriorParametersPooled setPriorParametersStratified getMuVar

Examples

 prior_parameters_berry <- setPriorParametersBerry(0, 1, 2)

bhmbasket documentation built on March 18, 2022, 7:46 p.m.